US 2007/0116343 A1 discloses a method for improving the quality of an image. A first image and a second image of a sample volume are reconstructed by applying one of a filtered backprojection method (FBP) and an iterative reconstruction method (IR), respectively. Based on a heuristic classifier that compares the CT number or Hounsfield Unit (HU) of each image element with a low and a high threshold, the first image is segmented into a soft-tissue region and a bone region with a smooth transition between the two regions. Additional classifiers can optionally be calculated by at least once low pass filtering the classifier used for segmentation. Moreover, if it is determined that the noise in the first image is high, a further additional “scaled down” classifier can optionally be calculated by multiplying an additional, two times low pass filtered classifier with a global scaling factor. One of the one or more classifiers is then used to generate a final image as a weighted average of the first image and the second image.
This generating of the final image has the drawback that the weighted averaging of the first image and the second image based on the provided one or more classifiers may still lead to a generated final image of inferior quality.